Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Stergios Poularakis"'
Autor:
Guendalina Cobianchi, Guido Meardi, Stergios Poularakis, Alexei Walisiewicz, Omran Abdelkafi, Foued Ben Amara, Faouzi Kossentini, Cosmin Stejerean, Hassene Tmar
Publikováno v:
Applications of Digital Image Processing XLV.
Autor:
Stefano Battista, Guido Meardi, Florian Maurer, Lorenzo Ciccarelli, Ahmad Byagowi, Stergios Poularakis, Guendalina Cobianchi, Simone Ferrara
Publikováno v:
Applications of Digital Image Processing XLIII.
Low Complexity Enhancement Video Coding (LCEVC) is a new MPEG video codec, currently undergoing standardization as MPEG-5 Part 2. Rather than being another video codec, LCEVC enhances any other codec (e.g. AVC, VP9, HEVC, AV1, EVC or VVC) to produce
Publikováno v:
IEEE Transactions on Cybernetics. 46:2094-2108
In this paper, we propose a complete gesture recognition framework based on maximum cosine similarity and fast nearest neighbor (NN) techniques, which offers high-recognition accuracy and great computational advantages for three fundamental problems
Publikováno v:
Pattern Recognition Letters. 79:31-37
Initializing LBKeogh Dynamic Time Warping search using the Euclidean Distance Nearest Neighbor.Employing a fast Nearest Neighbor algorithm (fastNN) to increase computational efficiency.Successful application on five gesture datasets.Requiring about 2
Publikováno v:
Signal Processing-Image Communication, 53, 1-12. Elsevier
This work proposes a framework for the efficient recognition of activities of daily living (ADLs), captured by static color cameras, applicable in real world scenarios. Our method reduces the computational cost of ADL recognition in both compressed a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::714d0d6d2d3ae1c20b0379005790b1b7
https://cris.maastrichtuniversity.nl/en/publications/0fae9551-6831-4515-8701-e30b11ed6db2
https://cris.maastrichtuniversity.nl/en/publications/0fae9551-6831-4515-8701-e30b11ed6db2
Publikováno v:
ICIP
In this work, we propose a computationally efficient method for the recognition of human activities of daily living. Our method uses trajectories of tracked visual features extracted on dense grids and performs recognition via Support Vector Machines
Publikováno v:
ICASSP
In this work, we propose a novel framework for automatic finger detection and hand posture recognition, based mainly on depth information. Our method locates apex-shaped structures in a hand contour and deals efficiently with the challenging problem
Publikováno v:
ICASSP
Dynamic recognition of gestures from video sequences is a challenging task due to the high variability in the characteristics of each gesture with respect to different individuals. In this work, we propose a novel representation of gestures as linear
Publikováno v:
WIAMIS
Motion analysis is an important component of surveillance, video annotation and many other applications. Current work focuses on the tracking of moving entities, the representation of their actions and the classification of sequences. A wide range of